Abstract: We present a principled design approach for building data
visualizations informed by only little, or no data. This approach is
inspired by graphic design practice and theory, and the development of a
parametric toolkit. It contrasts with standard approaches that are
“data-first” which suggest to initiate the visualization process only when
data are available, clean and well-formatted. Those usually are time
consuming and shift the focus from design to technical consideration. Our
approach is “design-first” by working on the graphical space (i.e. the
visualization canvas) with iterative subdivisions that progressively are
informed with more and realistic data. We will present numerous case
studies and an online tool which is publicly available to create
low-fidelity mock-ups using D3.js, and rendered in SVG, Canvas and WebGL.